Landing Phase Research Articles

A New Frontier in Wind Shear Intensity Forecasting: Stacked Temporal Convolutional Networks and Tree-Based Models Framework

Wind shear presents a considerable hazard to aviation safety, especially during the critical phases of takeoff and landing. Accurate forecasting of wind shear events is essential to mitigate these risks and improve both flight safety and operational efficiency. This paper introduces a hybrid Temporal Convolutional Networks and Tree-Based Models (TCNs-TBMs) framework specifically designed for time series modeling and the prediction of wind shear intensity. The framework utilizes the ability of TCNs to capture intricate temporal patterns and integrates it with the predictive strengths of TBMs, such as Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Categorical Boosting (CatBoost), resulting in robust forecast. To ensure optimal performance, hyperparameter tuning was performed using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), enhancing predictive accuracy. The effectiveness of the framework is validated through comparative analyses with standalone machine learning models such as XGBoost, RF, and CatBoost. The proposed TCN-XGBoost model outperformed these alternatives, achieving a lower Root Mean Squared Error (RMSE: 1.95 for training, 1.97 for testing), Mean Absolute Error (MAE: 1.41 for training, 1.39 for testing), and Mean Absolute Percentage Error (MAPE: 7.90% for training, 7.89% for testing). Furthermore, the uncertainty analysis demonstrated the model’s reliability, with a lower mean uncertainty (7.14 × 10−8) and standard deviation of uncertainty (6.48 × 10−8) compared to other models. These results highlight the potential of the TCNs-TBMs framework to significantly enhance the accuracy of wind shear intensity predictions, emphasizing the value of advanced time series modeling techniques for risk management and decision-making in the aviation industry. This study highlights the framework’s broader applicability to other meteorological forecasting tasks, contributing to aviation safety worldwide.

The effect of simulated basketball game load on patellar tendon load during stop-jump movement

Patellar tendinopathy (PT) is frequently observed among basketball players, particularly in sports involving repetitive jumping movements. However, the overall impact of accumulated exercise load on the patellar tendon is still not fully comprehended. Therefore, the goal of this study is to examine how a simulated basketball game affects the biomechanics of stop-jump movements, specifically focusing on the effects on the patellar tendon. The kinematic and kinetic data were collected immediately after the warm-up and each phase of the simulated basketball game (P1, P2, P3, and P4). A musculoskeletal model was built to calculate patellar tendon force (PTF) and the key biomechanical metrics during the horizontal landing and vertical jumping phases were explored separately, followed by correlation analyses. Linear regression analyses were performed on variables strongly correlated with PTF. The accumulation of load led to significant differences (p < 0.05) in the angles, velocities, torques, work contributions, peak patellar tendon force (PTF), and anterior-posterior ground reaction force (APGRF) observed during the landing and vertical jump phases at the hip, knee, and ankle joints. PTF showed strong correlations with knee flexion angle, knee extension angular velocity, ankle plantarflexion angular velocity, and APGRF, with R2 values of 0.50, 0.58, 0.70, and 0.56, respectively. PTF significantly decreased in P3 and P4, possibly due to the subjects’ adaptation and adjustment of their stop-jump posture strategy after load accumulation, including reducing knee and hip flexion angles and decreasing the net knee extension moment.

Coupling of Advanced Guidance and Robust Control for the Descent and Precise Landing of Reusable Launchers

This paper investigates the coupling of successive convex optimization guidance with robust structured H∞ control for the descent and precise landing of Reusable Launch Vehicles (RLVs). More particularly, this Guidance and Control (G&C) system is foreseen to be integrated into a nonlinear six-degree-of-freedom RLV controlled dynamics simulator which covers the aerodynamic and powered descent phase until vertical landing of a first-stage rocket equipped with a thrust vector control system and steerable planar fins. A cost function strategy analysis is performed to find out the most efficient one to be implemented in closed-loop with the robust control system and the vehicle flight mechanics involved. In addition, the controller synthesis via structured H∞ is thoroughly described. The latter are built at different points of the descent trajectory using Proportional-Integral-Derivative (PID)-like structures with feedback on the attitude angles, rates, and lateral body velocities. The architecture is verified through linear analyses as well as nonlinear cases with the aforementioned simulator, and the G&C approach is validated by comparing the performance and robustness with a baseline system in nominal conditions as well as in the presence of perturbations. The overall results show that the proposed G&C system represents a relevant candidate for realistic descent flight and precise landing phase for reusable launchers.

A bio-inspired looming detection for stable landing in unmanned aerial vehicles.

Flying insects, such as flies and bees, have evolved the capability to rely solely on visual cues for smooth and secure landings on various surfaces. In the process of carrying out tasks, micro unmanned aerial vehicles (UAVs) may encounter various emergencies, and it is necessary to land safely in complex and unpredictable ground environments, especially when altitude information is not accurately obtained, which undoubtedly poses a significant challenge. Our study draws on the remarkable response mechanism of the Lobula Giant Movement Detector to looming scenarios to develop a novel UAV landing strategy. The proposed strategy does not require distance estimation, making it particularly suitable for payload-constrained micro aerial vehicles. Through a series of experiments, this strategy has proven to effectively achieve stable and high-performance landings in unknown and complex environments using only a monocular camera. Furthermore, a novel mechanism to trigger the final landing phase has been introduced, further ensuring the safe and stable touchdown of the drone.

Impact of Quadriceps Muscle Fatigue on Ankle Joint Compensation Strategies During Single-Leg Vertical Jump Landing.

This study investigates the impact of quadriceps fatigue on lower limb biomechanics during the landing phase of a single-leg vertical jump (SLJ) in 25 amateur male basketball players from Ningbo University. Fatigue was induced through single-leg knee flexion and extension exercises until task failure. Kinematic and dynamic data were collected pre-fatigue (PRF) and post-fatigue (POF) using the Vicon motion capture system and the AMTI force platform and analyzed using an OpenSim musculoskeletal model. Paired sample t-tests revealed significant changes in knee and hip biomechanics under different fatigue conditions, with knee joint angle (p < 0.001), velocity (p = 0.006), moment (p = 0.006), and power (p = 0.036) showing significant alterations. Hip joint angle (p = 0.002), moment (p = 0.033), and power (p < 0.001) also exhibited significant changes. Muscle activation and joint power were significantly higher in the POF condition, while joint stiffness was lower. These findings suggest that quadriceps fatigue leads to biomechanical adjustments in the knee and hip joints, which may increase the risk of injury despite aiding in landing stability.

Skittering locomotion in cricket frogs: a form of porpoising.

Multiple species of frogs in the Ranidae family have been observed to 'skitter' across the water surface, but little is understood about the biomechanical or physical mechanisms that underlie this behavior. All documented descriptions are anecdotal, asserting simply that the frogs can cross the water surface without sinking. To study this form of interfacial locomotion, we recorded high speed video of the northern cricket frog Acris crepitans and quantified its kinematics. We also compared its semi-aquatic behavior with the frogs' terrestrial locomotion. Contrary to expectations based on anecdotal knowledge, we found that cricket frogs do not maintain an above-surface position throughout the locomotor cycle. Instead, the frogs are completely submerged during both the launching and landing phase of a jump cycle, similar to porpoising in other animals. It is possible that leg-retraction time constrains these frogs from performing true surface-only locomotion.

Redundancy Design of FADS System for Complex Leading- Edge Aircraft Based on Neural Network

The flush airdata sensing system (FADS) calculates flight parameters such as angle of attack, sideslip angle, Mach number, incoming flow pressure and static pressure based on the pressure measurement of the aircraft surface. It can effectively solve the problem that the leading edge of the pitot tube protruding from the fuselage cannot adapt to the severe aerodynamic heating faced by hypersonic aircraft during the cruise phase, and at the same time meet the aircraft's demand for stealth performance. At present, there is little analysis and research on the use of neural network methods and FADS systems for complex leading edge aircraft. In view of the subsonic/transonic conditions of hypersonic aircraft returning autonomously during the landing phase, the redundancy design and verification of the head FADS system of complex leading edge aircraft are carried out considering the influence of thin leading edge and inlet components. 15 pressure measuring holes are opened in the head of the complex leading edge aircraft. Through a large number of refined numerical simulations, the pressure database of the aircraft under different incoming flow conditions is established, and the typical working conditions are verified by wind tunnel tests. For the complex leading edge aircraft, 4 sets of neural network algorithms are established based on pressure data and redundant design research is carried out, including 1 set of 9-hole algorithm and 3 sets of redundant algorithms. Among them, the 9-hole algorithm has a higher accuracy, with the solution error of the angle of attack within 0.07∘, the solution error of the sideslip angle within 0.3∘, the solution error of the Mach number within 0.0012, and the relative error of the solution of the incoming flow pressure and static pressure within 1.5%. In addition, a system solution process with a certain fault tolerance was established, which can continue to maintain the effective output of the incoming flow parameters in the event of failure of any single pressure measuring hole.

Analysis on pulse rate variability for pilot workload assessment based on wearable sensor

AbstractThe workload levels of pilots directly affect their flight performance and the safety of the whole flight. To explore the real‐time workload of pilots in different flight phases (takeoff, cruise, and landing), this paper leveraged National Aeronautics and Space Administration Task Load Index (NASA‐TLX), a subjective evaluation scale, and PhotoPlethysmoGraphy (PPG) signals of 21 participants using a flight simulator and a wearable sensor. First, the workloads of pilots under different phases were explored by the NASA‐TLX scales; secondly, the pulse rate variability (PRV) features were selected by variance analysis and random forest importance evaluation; finally, the performances of the k‐nearest neighbor (KNN), random forest (RF), and support vector machine (SVM) were compared for workload levels identification. It is shown that the workloads are ranked as follows: landing &gt; takeoff &gt; cruise. SDNN, CVCD, CVNNI, LF, TP, SD2, and SD2/SD1 were used as selected features with significant differences in different flight phases. In addition, machine learning models can effectively identify pilot workloads, and feature selection enhances the performance of both KNN and RF classifiers. The best identification of workload was achieved using the selected PRV features as inputs to the KNN classifier, with an average accuracy of 88.9%. Our results indicate that the KNN classifier and PRV features are suitable for identifying pilot workload. The pilot workload is highest during the landing phase, which provides a reference for flight safety management. The findings from this research could contribute to developing a robust pilot workload detection system and improve current flight operation safety regulations.

Spatiotemporal dynamics and transformation of the Parana State coastline: A 34-year analysis using RS, GIS, and machine learning

The coastal zone is a critical and vibrant area within coastal cities. Analyzing the changes in the coastal zone of Parana State helps determine the spatiotemporal evolution patterns and driving forces of this region, providing guidance for resource protection and utilization. This study employs remote sensing (RS), Geographic Information System (GIS), and Machine Learning techniques, using Landsat data sets with eight distinct scenes from 1990 to 2024, to extract and analyze the coastline. Specifically, methodologies such as Shoreline Extraction, the Coastline Diversity Index (CDI), and the Coastline Utilization Index (CUI) were applied to assess the coastline's characteristics. The spatiotemporal characteristics of the coastline development in Parana are meticulously examined to ensure accuracy. The findings reveal that: 1) Over the past 34 years, the coastline of Parana State has shown a consistent increasing trend. Natural coastlines have been declining by 45% annually, while artificial coastlines have been increasing by approximately 55% annually. 2) The nature of the shoreline is transitioning from natural to sea-reclamation, engineering-enhanced, and degraded forest. 3) The coastline changes have occurred in three phases: The Built-up Land phase, the Port Petrochemical phase, and the Reducing Coastal Erosion phase. Significant shoreline extension is observed near both biological and ecological coasts. 4) The primary factors influencing the coastline alterations in Parana State include natural forces, human activities, and regional policies. These insights into the spatiotemporal dynamics of the Parana coastline can inform better coastal management and conservation strategies.

Automatic Aircraft Landing System: A Review

The aircraft landing phase, marking the finishing of a flight plane, is a critical yet dangerous aerial maneuver. Even though it might seem simple, predicting the complexities of performance during landing presents a big challenge due to the dynamic characteristics of the phase, interaction with piloting methods, as well as inherent uncertainties in aerodynamics. Landing is executed in close proximity to the ground at reduced airspeed, the landing phase entails an escalated safety risk. Notably, incidents and accidents, particularly overruns where aircraft fail to slow sufficiently on the runway before landing, underscore the imperative for advanced landing technologies. This paper presents a comprehensive review of research spanning from 2000 to the present exploring smart techniques like fuzzy logic and machine learning, an array of control strategies ranging from classic PID control to sophisticated hybrid control approaches, and optimization procedures utilizing diverse optimization algorithms. The primary objective is to provide a comprehensive evaluation of the existing research landscape, offering insights that can propel the evolution of strategies for safer and more efficient landings and making sure the plane touches down safely.

Interpretable semi-supervised clustering enables universal detection and intensity assessment of diverse aviation hazardous winds

The identification of aviation hazardous winds is crucial and challenging in air traffic management for assuring flight safety, particularly during the take-off and landing phases. Existing criteria are typically tailored for special wind types, and whether there exists a universal feature that can effectively detect diverse types of hazardous winds from radar/lidar observations remains as an open question. Here we propose an interpretable semi-supervised clustering paradigm to solve this problem, where the prior knowledge and probabilistic models of winds are integrated to overcome the bottleneck of scarce labels (pilot reports). Based on this paradigm, a set of high-dimensional hazard features is constructed to effectively identify the occurrence of diverse hazardous winds and assess the intensity metrics. Verification of the paradigm across various scenarios has highlighted its high adaptability to diverse input data and good generalizability to diverse geographical and climate zones.

Building interfaces between unmanned aircraft systems (UAS), air traffic controllers (ATCo), and the national airspace system (NAS): A software training platform

Nowadays, the development of technologies that improve airspace operation in many aspects is essential since the importance of air transportation for society is increasing. The airspace, although, may become more complex considering the integration of these aircraft due to the issues regarding the social acceptance of autonomous systems (e.g., familiarity between Air Traffic Controller - ATCo - and Unmanned Aircraft System - UAS) and the uncertainty in terms of operation (e.g., hardware failures, software failures, interfaces failures, and misunderstanding of instructions). However, standard procedures (e.g., landing procedures) may not be followed in complex situations due to safety constraints (e.g., loss of minimum aircraft separation). As a result, ATCos play an essential role in maintaining appropriate levels of safety and efficiency by conducting aircraft using Vectoring Points (VPs). Hence, ATCos must be trained to deal with such challenging scenarios, especially in resource-constrained regions, e.g., in the final sector of the Terminal Control Area (TMA), where the aircraft are guided to the landing phase. The primary goal of this research is to propose a framework for training Air Traffic Controllers (ATCos) to deal with complex situations (e.g., considering many aircraft as well as severe weather conditions) in the final sector considering the UAS integration into the National Airspace System (NAS). This approach is divided into a set of modules for (1) proposing the training scenarios, (2) proposing solutions, and (3) evaluating the quality and feasibility of the solutions proposed. The aspects evaluated in the solutions provided for the proposed scenarios are ATCo workload and efficiency.

Effects of 16weeks of plyometric training on knee biomechanics during the landing phase in athletes.

This study investigated the effects of plyometric training on lower-limb muscle strength and knee biomechanical characteristics during the landing phase. Twenty-four male subjects were recruited for this study with a randomised controlled design. They were randomly divided into a plyometric training group and a traditional training group and underwent training for 16weeks. Each subject was evaluated every 8weeks for knee and hip isokinetic muscle strength as well as knee kinematics and kinetics during landing. The results indicated significant group and time interaction effects for knee extension strength (F=74.942 and p=0.001), hip extension strength (F=99.763 and p=0.000) and hip flexion strength (F=182.922 and p=0.000). For landing kinematics, there were significant group main effects for knee flexion angle range (F=4.429 and p=0.047), significant time main effects for valgus angle (F=6.502 and p=0.011) and significant group and time interaction effects for internal rotation angle range (F=5.475 and p=0.008). The group main effect for maximum knee flexion angle was significant (F=7.534 and p=0.012), and the group and time interaction effect for maximum internal rotation angle was significant (F=15.737 and p=0.001). For landing kinetics, the group main effect of the loading rate was significant (F=4.576 and p=0.044). Significant group and time interaction effects were observed for knee extension moment at the moment of maximum vertical ground reaction force (F=5.095 and p=0.010) and for abduction moment (F=8.250 and p=0.001). These findings suggest that plyometric training leads to greater improvements in hip and knee muscle strength and beneficial changes in knee biomechanics during landing compared to traditional training.

The Comparison of Electromyography (EMG) During Blocking in Elite Sepaktakraw Athletes

Background: Blocking is a major indicator of the sepaktakraw game’s results. The analysis of muscle activity involved in blocking provides coaches or amateur athletes with additional information about the importance of muscle groups that influence effective blocking. Objective: This research aimed to compare the maximum voluntary contraction (MVC)during blocking elite sepaktakraw athletes in different muscles. Methods: This research is a cross-sectional study design with fourteen male sepaktakraw athletes (striker position) in the Sepaktakraw Thailand League, aged 20-40 years. All participants completed an informed consent by the ethical committee of Thailand National Sports University (TNSU-SCI 043-2566), and were placed electrodes on five muscle groups, including the rectus abdominis (RA), left rectus femoris (LRF), left gastrocnemius medialis (LGM), right rectus femoris (RRF) and right gastrocnemius medialis (RGM). The collection of blocking is divided into 3 phases: takeoff, flight and landing. Results: The LGM had the highest and was significantly with RA in takeoff phase and landing phase (P0.05), RGM had the highest in flight phase and significantly different with takeoff (p0.05). Moreover, RA during flight and landing significantly differed from takeoff (p0.05). Conclusion: The information this research will help coaches and amateur athletes understanding the blocking in elite athletes. Additionally, they need a specific muscle training program.

The effects of fatigue on the relationship between ankle angle at initial contact and the knee and hip joints in landing: Assessing the risk of ACL injury

BackgroundAnterior cruciate ligament (ACL) injuries may correlate with lower limb angles and biomechanical factors in both dominant and non-dominant legs at initial contact (IC) post-landing. This study aims to investigate the correlation between ankle angles in three axes at IC and knee and hip joint angles during post-spike landings in professional volleyball players, both pre- and post-fatigue induction. Research questionTo what extent does fatigue influence lower limb joint angles, and what is the relationship between ankle joint angles and hip and knee angles at IC during the landing phase following a volleyball spike? MethodsUnder conditions involving the peripheral fatiguing protocol, the lower limb joint angles at IC following post-spike landings were measured in 28 professional male volleyball players aged between 19 and 28 years, who executed the Bosco fatigue protocol both before and after inducing fatigue. A paired t-test was utilized to compare the joint angles pre- and post-fatigue in both dominant and non-dominant legs. Furthermore, Pearson's correlation test was conducted to explore the relationship between ankle angles at IC and the corresponding knee and hip joint angles. ResultsThe findings of the study revealed that fatigue significantly increased hip external rotation and decreased knee joint flexion and external rotation in both the dominant and non-dominant legs (p < 0.05). Additionally, correlation analysis demonstrated that the ankle joint's positioning in the frontal and horizontal planes was significantly associated with hip flexion and external rotation at the IC, as well as with knee flexion and rotation (0.40 < r < 0.80). ConclusionFatigue increased hip external rotation and ankle internal rotation, weakening the correlation between these joints while strengthening the ankle-knee relationship, indicating a reduced hip control in jumps. This suggests a heightened ACL injury risk in the dominant leg due to the weakened ankle-hip connection, contrasting with the non-dominant leg.

Neuromuscular fatigue and cognitive constraints independently modify lower extremity landing biomechanics in healthy and chronic ankle instability individuals

ABSTRACT The purpose was to determine the impact of both cognitive constraint and neuromuscular fatigue on landing biomechanics in healthy and chronic ankle instability (CAI) participants. Twenty-three male volunteers (13 Control and 10 CAI) performed a single-leg landing task before and immediately after a fatiguing exercise with and without cognitive constraints. Ground Reaction Force (GRF) and Time to Stabilization (TTS) were determined at landing in vertical, anteroposterior (ap) and mediolateral (ml) axes using a force plate. Three-dimensional movements of the hip, knee and ankle were recorded during landing using a motion capture system. Exercise-induced fatigue decreased ankle plantar flexion and inversion and increased knee flexion. Neuromuscular fatigue decreased vertical GRF and increased ml GRF and ap TTS. Cognitive constraint decreased ankle internal rotation and increased knee and hip flexion during the flight phase of landing. Cognitive constraint increased ml GRF and TTS in all three axes. No interaction between factors (group, fatigue, cognitive) were observed. Fatigue and cognitive constraint induced greater knee and hip flexion, revealing higher proximal control during landing. Ankle kinematic suggests a protective strategy in response to fatigue and cognitive constraints. Finally, these two constraints impair dynamic stability that could increase the risk of ankle sprain.

Differences in Lower-Extremity Joint Coordination During Two Landing Phases of a Drop Jump Task.

The aim of the present study was to compare the differences in joint coordination patterns and variability in the lower extremity between the first and second landing phases of the drop jump. Eighteen resistance-trained men (age: 22.8 ± 1.8years) performed drop jumps from a height of 0.40m. An eight-camera motion capture system was utilized to record kinematic trajectories. Modified vector coding technique and circular statistics were used to determine the coordination pattern and variability of the following joint couples during the first and second landings: hip frontal-knee frontal (HfKf), hip sagittal-knee frontal (HsKf), hip sagittal-knee sagittal (HsKs), knee frontal-ankle frontal (KfAf), knee sagittal-ankle frontal (KsAf), and knee sagittal-ankle sagittal (KsAs). Statistical differences in the distribution frequencies of coupling angles and variability between the dominant and nondominant limbs across the two landing phases were compared using two-way repeated analysis of variance and Wilcoxon rank-sum tests. During the second landing phase, the proportion of HsKs, KfAf, and KsAs showing in-phase coordination was reduced but the proportion of KfAf and KsAs showing proximal joint (knee) coordination was increased (p < .05). Significant differences in bilateral asymmetry were observed only for the HfKf and KfAf patients (p < .05). HsKs, KfAf, and KsAf varied considerably during the second landing phase (p < .05). Joint coordination patterns during the second landing phase of the drop jump differed considerably from those during the first landing phase, thereby increasing the risk of knee and ankle injuries.

Design and simulation of system to prevent runway overrun during landing of civil aircraft

Abstract The airborne runway overrun prevention system predicts landing distance by utilizing real-time aircraft status parameters obtained through onboard sensors. This system offers early warnings to pilots, thereby enhancing flight safety. This paper introduces a design scheme for a runway overrun prevention system considering aircraft dynamic performance. Initially, the study analyzes the basic components and functional requirements of the system based on the Minimum Operational Performance Standard For A Runway Overrun Awareness And Alerting System by the European Aviation Safety Agency. Subsequently, the approach and landing phases are segmented into four stages, providing a methodology for calculating landing distance using a dynamic model. Finally, concluded with a simulation verification conducted on the X-Plane flight simulation platform, we test the visual alarm system of the proposed runway overrun prevention system. Simulation results demonstrate that, during the landing phase, the system dynamically calculates and updates stopping points for each braking mode based on the current braking method. In situations where there is a risk of runway overrun, the system issues timely and well-founded alarms.

Subseasonal Forecast Skill of Evaporative Demand, Soil Moisture, and Flash Drought Onset from Two Dynamic Models over the Contiguous United States

Abstract Flash droughts are rapidly developing subseasonal climate extreme events that are manifested as suddenly decreased soil moisture, driven by increased evaporative demand and/or sustained precipitation deficits. Over each climate region in the contiguous United States (CONUS), we evaluated the forecast skill of weekly root-zone soil moisture (RZSM), evaporative demand (ETo), and relevant flash drought (FD) indices derived from two dynamic models [Goddard Earth Observing System model V2p1 (GEOS-V2p1) and Global Ensemble Forecast System version 12 (GEFSv12)] in the Subseasonal Experiment (SubX) project between years 2000 and 2019 against three reference datasets: Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), North American Land Data Assimilation System, phase 2 (NLDAS-2), and GEFSv12 reanalysis. The ETo and its forcing variables at lead week 1 have moderate-to-high anomaly correlation coefficient (ACC) skill (∼0.70–0.95) except downwelling shortwave radiation, and by weeks 3–4, predictability was low for all forcing variables (ACC &lt; 0.5). RZSM (0–100 cm) for model GEFSv12 showed high skill at lead week 1 (∼0.7–0.85 ACC) in the High Plains, West, Midwest, and South CONUS regions when evaluated against GEFSv12 reanalysis but lower skill against MERRA-2 and NLDAS-2 and ACC skill are still close to 0.5 for lead weeks 3–4, better than ETo forecasts. GEFSv12 analysis has not been evaluated against in situ observations and has substantial RZSM anomaly differences when compared to NLDAS-2, and our analysis identified GEFSv12 reforecast prediction limit, which can maximally achieve ACC ∼0.6 for RZSM forecasts between lead weeks 3 and 4. Analysis of major FD events reveals that GEFSv12 reforecast inconsistently captured the correct location of atmospheric and RZSM anomalies contributing to FD onset, suggesting the needs for improving the dynamic models’ assimilation and initialization procedures to improve subseasonal FD predictability. Significance Statement Flash droughts are rapidly developing climate extremes which reduce soil moisture through enhanced evaporative demand and precipitation deficits, and these events can have large impacts on the ecosystem and crop health. We evaluated the subseasonal forecast skill of soil moisture and evaporative demand against three reanalysis datasets and found that evaporative demand skill was similar between forecasts and reanalyses while soil moisture skill is dependent on the reference dataset. Skill of evaporative demand decreases rapidly after week 1, while soil moisture skill declines more slowly after week 1. Case studies for the 2012, 2017, and 2019 United States flash droughts identified that forecasts could capture rapid decreases in soil moisture in some regions but not consistently, implying that long-lead forecasts still need improvements before being used in early warning systems. Improvements in flash drought predictability at longer lead times will require less biased initial conditions, better model parameterizations, and improved representations of large-scale teleconnections.

Interference Study of 5G System on Civil Aircraft Airborne Beidou RDSS System in Takeoff and Landing Phase

Interference Study of 5G System on Civil Aircraft Airborne Beidou RDSS System in Takeoff and Landing Phase